{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\swhitt\Desktop\EJPR Poland Replication Data\EJPR Poland replication log file.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}14 Mar 2025, 09:14:36

{com}. do "C:\Users\swhitt\Desktop\EJPR Poland Replication Data\EJPR Poland replication do file.do"
{txt}
{com}. *Replication Instructions for
. 
. *Anti-LGBT Messaging and Electoral Outcomes under the Shadow of War: Evidence from the 2023 Polish Parliamentary Election. 
. 
. *Phillip Ayoub, Douglas Page, Sam Whitt
. 
. 
. *Below are instructions for replicating all manuscript and online appendix tables and figures in STATA using the dataset "EJPR Poland replication data". Please contact Sam Whitt (swhitt@highpoint.edu) for questions regarding data replication. See also the dofile "EJPR Poland replication do file". 
. 
. *Note: You may need to install STATA packages for the cibar, catcibar, and iebaltab commands. Use findit with the command name to identify and download the appropriate packets to install. 
. 
. *Note: In addition, some graphs require additional formatting using filename.grec files with the graph play command. To format a graph, simply run the command to generate the graph in the do file in STATA, then open the "Graph Editor" in STATA and click on the GREEN "Play Recording" button, then select "Browse" to select the grec file from the folder "grec files for STATA graph formatting" among Replication files. The name of the grec file is indicated in the note below the graph command in the do file for the specific graph you wish to format. This should automatically format the graph, which you may then save to a location of your choosing.
. 
. *Manuscript Replication
. 
. *"Stata user generated commands to install for replication purposes"
. 
. *"cibar"
. 
. ssc install cibar, replace
{txt}checking {hilite:cibar} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. *"iebaltab from ietoolkit"
. 
. ssc install ietoolkit, replace
{txt}checking {hilite:ietoolkit} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. *"catcibar"
. 
. net install catcibar, from("https://aarondwolf.github.io/catcibar") replace
checking {hilite:catcibar} consistency and verifying not already installed...
all files already exist and are up to date.
{txt}
{com}. 
. *"marginscontplot and marginscontplot2"
. 
. net install gr0056, from(http://www.stata-journal.com/software/sj13-3) replace
checking {hilite:gr0056} consistency and verifying not already installed...
all files already exist and are up to date.
{txt}
{com}. ssc install marginscontplot2, replace
{txt}checking {hilite:marginscontplot2} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. *"interflex"
. 
. ssc install interflex
{txt}checking {hilite:interflex} consistency and verifying not already installed...
all files already exist and are up to date.

{com}. 
. *Figure 2
. 
. histogram revvotepisduda , discrete percent addlabels addlabopts(mlabformat(%2.1f))
{txt}(start={res}1{txt}, width={res}1{txt})
{res}{txt}
{com}. graph save g1
{res}{txt}file {bf:g1.gph} saved

{com}. histogram revvotepotusk , discrete percent addlabels addlabopts(mlabformat(%2.1f))
{txt}(start={res}1{txt}, width={res}1{txt})
{res}{txt}
{com}. graph save g2
{res}{txt}file {bf:g2.gph} saved

{com}. histogram tuskbias3, discrete percent addlabels addlabopts(mlabformat(%2.1f))
{txt}(start={res}-1{txt}, width={res}1{txt})
{res}{txt}
{com}. graph save g3
{res}{txt}file {bf:g3.gph} saved

{com}. 
. graph combine "g1.gph" "g2.gph" "g3.gph"
{res}{txt}
{com}. 
. *refer to "Figure 2 formatting.grec" file to format the resulting combined graph.
. 
. *Table 2
. 
. reg dvoteduda i.experiment2, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}     0.47
                                                {txt}Prob > F          = {res}    0.7023
                                                {txt}R-squared         = {res}    0.0015
                                                {txt}Root MSE          =    {res} .45199

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0051084{col 41}{space 2} .0400371{col 52}{space 1}   -0.13{col 61}{space 3}0.898{col 69}{space 4}-.0836752{col 82}{space 3} .0734584
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0376326{col 41}{space 2} .0408712{col 52}{space 1}    0.92{col 61}{space 3}0.357{col 69}{space 4} -.042571{col 82}{space 3} .1178362
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.0011084{col 41}{space 2} .0401277{col 52}{space 1}   -0.03{col 61}{space 3}0.978{col 69}{space 4} -.079853{col 82}{space 3} .0776361
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .2771084{col 41}{space 2} .0284205{col 52}{space 1}    9.75{col 61}{space 3}0.000{col 69}{space 4} .2213375{col 82}{space 3} .3328794
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvotetusk i.experiment2, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}     4.22
                                                {txt}Prob > F          = {res}    0.0056
                                                {txt}R-squared         = {res}    0.0130
                                                {txt}Root MSE          =    {res} .48684

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvotetusk{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0025703{col 41}{space 2} .0430278{col 52}{space 1}    0.06{col 61}{space 3}0.952{col 69}{space 4}-.0818652{col 82}{space 3} .0870058
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0170723{col 41}{space 2} .0431637{col 52}{space 1}    0.40{col 61}{space 3}0.693{col 69}{space 4}-.0676299{col 82}{space 3} .1017745
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1345703{col 41}{space 2}   .04393{col 52}{space 1}    3.06{col 61}{space 3}0.002{col 69}{space 4} .0483642{col 82}{space 3} .2207763
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .3574297{col 41}{space 2} .0304317{col 52}{space 1}   11.75{col 61}{space 3}0.000{col 69}{space 4} .2977121{col 82}{space 3} .4171473
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias i.experiment2, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}     2.74
                                                {txt}Prob > F          = {res}    0.0423
                                                {txt}R-squared         = {res}    0.0082
                                                {txt}Root MSE          =    {res} .49683

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dtuskbias{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0343775{col 41}{space 2}  .044291{col 52}{space 1}    0.78{col 61}{space 3}0.438{col 69}{space 4}-.0525368{col 82}{space 3} .1212919
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0366086{col 41}{space 2} .0442583{col 52}{space 1}    0.83{col 61}{space 3}0.408{col 69}{space 4}-.0502417{col 82}{space 3} .1234589
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1223775{col 41}{space 2} .0444185{col 52}{space 1}    2.76{col 61}{space 3}0.006{col 69}{space 4}  .035213{col 82}{space 3}  .209542
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .4056225{col 41}{space 2}  .031179{col 52}{space 1}   13.01{col 61}{space 3}0.000{col 69}{space 4} .3444383{col 82}{space 3} .4668067
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *in Model 2 we observe that linking anti-LGBTIQ rhetoric to the war in Ukraine resulted in a 13% increase in support for PO/Tusk (unpaired t-test=3.06, p<0.002) 
. 
. ttest dvotetusk if experiment2~=2 & experiment2~=3, by(ukrainetxt) unpaired unequal

{txt}Two-sample t test with unequal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    249{col 22} .3574297{col 34}  .030432{col 46} .4802081{col 58} .2974917{col 70} .4173678
       {txt}1 {c |}{res}{col 12}    250{col 22}     .492{col 34} .0316822{col 46} .5009389{col 58} .4296008{col 70} .5543992
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    499{col 22} .4248497{col 34}  .022151{col 46} .4948162{col 58} .3813287{col 70} .4683707
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.1345703{col 34} .0439302{col 58}-.2208824{col 70}-.0482582
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -3.0633
{txt}H0: diff = 0                     Satterthwaite's degrees of freedom = {res} 496.275

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0012         {txt}Pr(|T| > |t|) = {res}0.0023          {txt}Pr(T > t) = {res}0.9988
{txt}
{com}. 
. *Figure 3
. 
. interflex dtuskbias ukrainetxt revcontactgay, type(kernel) bw(0.80) vce(robust)
{res}{txt}
{com}. graph save g4.gph
{res}{txt}file {bf:g4.gph} saved

{com}. interflex dtuskbias ukrainetxt closegay, type(kernel) bw(2.5) vce(robust)
{res}{txt}
{com}. graph save g5.gph
{res}{txt}file {bf:g5.gph} saved

{com}. interflex dtuskbias ukrainetxt supportrights, type(kernel) bw(1) vce(robust)
{res}{txt}
{com}. graph save g6.gph
{res}{txt}file {bf:g6.gph} saved

{com}. interflex dtuskbias ukrainetxt putinfav, type(kernel) bw(2.8)  vce(robust)
{res}{txt}
{com}. graph save g7.gph
{res}{txt}file {bf:g7.gph} saved

{com}. interflex dtuskbias ukrainetxt russiadefeat, type(kernel) bw(8.9) vce(robust)
{res}{txt}
{com}. graph save g8.gph
{res}{txt}file {bf:g8.gph} saved

{com}. interflex dtuskbias ukrainetxt dudafav, type(kernel) bw(1)  vce(robust)
{res}{txt}
{com}. graph save g9.gph
{res}{txt}file {bf:g9.gph} saved

{com}. 
. graph combine "g4.gph" "g5.gph" "g6.gph" "g7.gph" "g8.gph" "g9.gph"
{res}{txt}
{com}. 
. *use "Figure 3 formatting.grec" file to format the resulting combined graph.
. 
. *Appendix Replication
. 
. *Appendix Figure. Likelihood of Voting for PiS vs. PO
. 
. catcibar dvotetusk dvoteduda, over(experiment2)
{txt}
{com}. 
. *Appendix Figure. Favorable Views of Duda
. 
. catcibar dudafav, over(experiment2)
{txt}
{com}. 
. *Appendix Figure: LGBT+ Rights Support by Likelihood of Voting for PiS/Duda
. 
. cibar supportrights, over1(experiment2) over2(dvoteduda)
{res}{txt}
{com}. 
. *Descriptive Statistics
. 
. sum livefree supportrights closegay russiadefeat dudafav putinfav revukrainefav revcontactgay revimpreligion revimpnationality age education

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}livefree {c |}{res}      1,000       7.355    3.086503          0         10
{txt}supportrig~s {c |}{res}      1,000       5.797    3.343197          0         10
{txt}{space 4}closegay {c |}{res}      1,000       3.244    3.150617          0         10
{txt}russiadefeat {c |}{res}      1,000       8.787    2.351842          0         10
{txt}{space 5}dudafav {c |}{res}      1,000       3.778    3.253198          0         10
{txt}{hline 13}{c +}{hline 57}
{space 4}putinfav {c |}{res}      1,000        .783    1.805317          0         10
{txt}revukraine~v {c |}{res}      1,000       2.648    .7941831          1          4
{txt}revcontact~y {c |}{res}      1,000       2.807    1.277256          1          5
{txt}revimpreli~n {c |}{res}      1,000       2.668     1.05018          1          4
{txt}revimpnati~y {c |}{res}      1,000       3.304    .7925984          1          4
{txt}{hline 13}{c +}{hline 57}
{space 9}age {c |}{res}      1,000      40.585    13.20656         18         65
{txt}{space 3}education {c |}{res}      1,000        2.94    .9204603          1          4
{txt}
{com}. 
. tab dvoteduda

  {txt}dummy for {c |}
 likely PiS {c |}
     voters {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        715       71.50       71.50
{txt}          1 {c |}{res}        285       28.50      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. tab dvotetusk

  {txt}dummy for {c |}
  likely PO {c |}
    voters  {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        604       60.40       60.40
{txt}          1 {c |}{res}        396       39.60      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. tab dtuskbias

      {txt}dummy {c |}
   variable {c |}
   for tusk {c |}
       bias {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        546       54.60       54.60
{txt}          1 {c |}{res}        454       45.40      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. tab female

     {txt}female {c |}
      dummy {c |}
   variable {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        500       50.00       50.00
{txt}          1 {c |}{res}        500       50.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. tab region

              {txt}Region: {c |}      Freq.     Percent        Cum.
{hline 22}{c +}{hline 35}
      Region 1: South {c |}{res}        203       20.30       20.30
{txt} Region 2: north-west {c |}{res}        166       16.60       36.90
{txt} Region 3: South-west {c |}{res}        104       10.40       47.30
{txt}      Region 4: north {c |}{res}        145       14.50       61.80
{txt}    Region 5: central {c |}{res}         93        9.30       71.10
{txt}    Region 6: eastern {c |}{res}        148       14.80       85.90
{txt}   Region 7: Masovian {c |}{res}        141       14.10      100.00
{txt}{hline 22}{c +}{hline 35}
                Total {c |}{res}      1,000      100.00
{txt}
{com}. tab urban

                        {txt}respondent town {c |}      Freq.     Percent        Cum.
{hline 40}{c +}{hline 35}
                                Village {c |}{res}        398       39.80       39.80
{txt}     City with up to 20,000 inhabitants {c |}{res}         93        9.30       49.10
{txt} City between 20,000 and 100,000 inhabi {c |}{res}        223       22.30       71.40
{txt} City with 100,000 to 500,000 inhabitan {c |}{res}        176       17.60       89.00
{txt} City with more than 500,000 inhabitant {c |}{res}        110       11.00      100.00
{txt}{hline 40}{c +}{hline 35}
                                  Total {c |}{res}      1,000      100.00
{txt}
{com}. tab employment

                          {txt}employment {c |}      Freq.     Percent        Cum.
{hline 37}{c +}{hline 35}
 I work under an employment contract {c |}{res}        555       55.50       55.50
{txt}        I have a contract of mandate {c |}{res}         63        6.30       61.80
{txt} I have a contract for specific work {c |}{res}         13        1.30       63.10
{txt}                       Self-employed {c |}{res}         37        3.70       66.80
{txt}              Not currently employed {c |}{res}         69        6.90       73.70
{txt}        Pensioner{c -(}a:{c )-} Pensioner{c -(}k:{c )-}a {c |}{res}        102       10.20       83.90
{txt}                 {c -(}Pupil{c )-} or student{c )-} {c |}{res}         69        6.90       90.80
{txt}       I am involved in housekeeping {c |}{res}         78        7.80       98.60
{txt}                               Other {c |}{res}         14        1.40      100.00
{txt}{hline 37}{c +}{hline 35}
                               Total {c |}{res}      1,000      100.00
{txt}
{com}. tab experiment2

          {txt}1=control, 2=duda, {c |}
               3=duda+putin, {c |}
            4=duda+putin+war {c |}      Freq.     Percent        Cum.
{hline 29}{c +}{hline 35}
                     control {c |}{res}        249       24.90       24.90
{txt}          domestic messenger {c |}{res}        250       25.00       49.90
{txt}    domestic messenger+putin {c |}{res}        251       25.10       75.00
{txt}domestic messenger+putin+war {c |}{res}        250       25.00      100.00
{txt}{hline 29}{c +}{hline 35}
                       Total {c |}{res}      1,000      100.00
{txt}
{com}. tab leftright3

   {txt}<5 left, {c |}
5=moderate, {c |}
   >5right  {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        288       28.80       28.80
{txt}          2 {c |}{res}        404       40.40       69.20
{txt}          3 {c |}{res}        308       30.80      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,000      100.00
{txt}
{com}. 
. *Randomization and Covariate Balance
. 
. iebaltab female age education region urban employment leftright revimpreligion revimpnationality livefree russiafav ukrainefav, groupvar(experiment2) control(1) savexlsx(polandbalance)

{res}{phang}Balance table saved in Excel format to: {browse "polandbalance.xlsx":polandbalance.xlsx}{p_end}
{txt}
{com}. 
. *Likelihood of Voting for PO/Tusk (OLS Regression)
. 
. reg dvotetusk ukrainetxt if experiment2~=2 & experiment2~=3, robust

{txt}Linear regression                               Number of obs     = {res}       499
                                                {txt}F(1, 497)         =  {res}     9.38
                                                {txt}Prob > F          = {res}    0.0023
                                                {txt}R-squared         = {res}    0.0185
                                                {txt}Root MSE          =    {res}  .4907

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2} .1345703{col 26}{space 2} .0439302{col 37}{space 1}    3.06{col 46}{space 3}0.002{col 54}{space 4} .0482585{col 67}{space 3} .2208821
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3574297{col 26}{space 2} .0304318{col 37}{space 1}   11.75{col 46}{space 3}0.000{col 54}{space 4} .2976388{col 67}{space 3} .4172206
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvotetusk ukrainetxt leftright if experiment2~=2 & experiment2~=3, robust

{txt}Linear regression                               Number of obs     = {res}       499
                                                {txt}F(2, 496)         =  {res}    47.98
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1357
                                                {txt}Root MSE          =    {res} .46094

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2} .1000295{col 26}{space 2} .0417647{col 37}{space 1}    2.40{col 46}{space 3}0.017{col 54}{space 4}  .017972{col 67}{space 3}  .182087
{txt}{space 3}leftright {c |}{col 14}{res}{space 2} -.073535{col 26}{space 2} .0082267{col 37}{space 1}   -8.94{col 46}{space 3}0.000{col 54}{space 4}-.0896985{col 67}{space 3}-.0573715
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7567039{col 26}{space 2}  .057922{col 37}{space 1}   13.06{col 46}{space 3}0.000{col 54}{space 4} .6429012{col 67}{space 3} .8705066
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvotetusk ukrainetxt##c.leftright if experiment2~=2 & experiment2~=3, robust

{txt}Linear regression                               Number of obs     = {res}       499
                                                {txt}F(3, 495)         =  {res}    35.07
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1400
                                                {txt}Root MSE          =    {res} .46027

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}             dvotetusk{col 24}{c |} Coefficient{col 36}  std. err.{col 48}      t{col 56}   P>|t|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}1.ukrainetxt {c |}{col 24}{res}{space 2} .2455395{col 36}{space 2} .1008016{col 47}{space 1}    2.44{col 56}{space 3}0.015{col 64}{space 4} .0474878{col 77}{space 3} .4435913
{txt}{space 13}leftright {c |}{col 24}{res}{space 2}-.0597497{col 36}{space 2} .0121787{col 47}{space 1}   -4.91{col 56}{space 3}0.000{col 64}{space 4} -.083678{col 77}{space 3}-.0358213
{txt}{space 22} {c |}
ukrainetxt#c.leftright {c |}
{space 20}1  {c |}{col 24}{res}{space 2}-.0280312{col 36}{space 2} .0161036{col 47}{space 1}   -1.74{col 56}{space 3}0.082{col 64}{space 4}-.0596711{col 77}{space 3} .0036087
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} .6818535{col 36}{space 2} .0786355{col 47}{space 1}    8.67{col 56}{space 3}0.000{col 64}{space 4}  .527353{col 77}{space 3} .8363541
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. teffects psmatch (dvotetusk) (ukrainetxt leftright) if experiment2~=2 & experiment2~=3, vce(iid)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       499
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         3
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}        102
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 2}ukrainetxt {c |}
{space 3}(1 vs 0)  {c |}{col 14}{res}{space 2} .0947143{col 26}{space 2} .0408579{col 37}{space 1}    2.32{col 46}{space 3}0.020{col 54}{space 4} .0146343{col 67}{space 3} .1747944
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Sensitivity Analysis
. 
. reg dvotetusk ukrainetxt leftright, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(2, 997)         =  {res}    97.56
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1353
                                                {txt}Root MSE          =    {res} .45547

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2} .1083829{col 26}{space 2} .0336298{col 37}{space 1}    3.22{col 46}{space 3}0.001{col 54}{space 4} .0423896{col 67}{space 3} .1743761
{txt}{space 3}leftright {c |}{col 14}{res}{space 2}-.0754505{col 26}{space 2}  .005778{col 37}{space 1}  -13.06{col 46}{space 3}0.000{col 54}{space 4} -.086789{col 67}{space 3} -.064112
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7578516{col 26}{space 2} .0381839{col 37}{space 1}   19.85{col 46}{space 3}0.000{col 54}{space 4} .6829216{col 67}{space 3} .8327816
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. regsensitivity bounds dvotetusk ukrainetxt female age education i.region i.urban i.employment leftright revimpreligion revimpnationality revcontactgay livefree revrussiafav revukrainefav if experiment2~=2 & experiment2~=3, compare(leftright)
{res}
{txt}{ul:Regression Sensitivity Analysis, Bounds}

Analysis{col 18}{res}: DMP (2022){col 48}{txt}Number of obs{col 67}{res}=         499
{col 48}{txt}Beta(short){col 67}{res}=       0.104
{txt}Treatment{col 18}{res}: ukrainetxt{col 48}{txt}Beta(medium){col 67}{res}=       0.090
{txt}Outcome{col 18}{res}: dvotetusk{col 48}{txt}R2(short){col 67}{res}=       0.013
{col 48}{txt}R2(medium){col 67}{res}=       0.063
{col 48}{txt}Var(Y){col 67}{res}=       0.193
{col 48}{txt}Var(X){col 67}{res}=       0.234
{col 48}{txt}Var(X_Residual){col 67}{res}=       0.233

{txt}Hypothesis{col 18}{res}: Beta > 0         {col 48}{txt}Breakdown point{col 67}{res}=        82.8%
{txt}Other Params{col 18}{res}: cbar = 1, rybar = +inf

{txt}{hline 80}
 rxbar{col 35} Beta
{hline 80}
{res}{col 2}0.000{col 35}{txt}[{res} 0.0899{txt}, {res} 0.0899{txt} ]
{col 2}{res}0.103{col 35}{txt}[{res} 0.0836{txt}, {res} 0.0962{txt} ]
{col 2}{res}0.206{col 35}{txt}[{res} 0.0772{txt}, {res} 0.1027{txt} ]
{col 2}{res}0.309{col 35}{txt}[{res} 0.0702{txt}, {res} 0.1096{txt} ]
{col 2}{res}0.412{col 35}{txt}[{res} 0.0625{txt}, {res} 0.1173{txt} ]
{col 2}{res}0.515{col 35}{txt}[{res} 0.0535{txt}, {res} 0.1264{txt} ]
{col 2}{res}0.618{col 35}{txt}[{res} 0.0422{txt}, {res} 0.1376{txt} ]
{col 2}{res}0.721{col 35}{txt}[{res} 0.0267{txt}, {res} 0.1531{txt} ]
{col 2}{res}0.823{col 35}{txt}[{res} 0.0014{txt}, {res} 0.1784{txt} ]
{col 2}{res}0.926{col 35}{txt}[{res}-0.0615{txt}, {res} 0.2413{txt} ]
{col 2}{res}0.998{col 35}{txt}[   {res}-inf{txt},    {res}+inf{txt} ]
{hline 80}

{com}. 
. *Power calculations
. 
.  power oneway, n(1000) power(0.8 0.9 0.95 0.99) ngroups(4)
{res}
{txt}Performing iteration ...
{res}
{p 0 2 2}{txt}Estimated{txt} between-group variance{txt} for one-way ANOVA{p_end}{txt}F test for group effect
{txt}{txt}{bind:H0: delta = 0}  {txt}versus  {bind:Ha: delta != 0}

  {txt}{c TLC}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 12}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 1}{c TRC}
  {txt}{c |}{txt}{txt}{ralign 8:alpha}{txt}{txt}{ralign 8:power}{txt}{txt}{ralign 8:N}{txt}{txt}{ralign 12:N_per_group}{txt}{txt}{ralign 8:delta}{txt}{txt}{ralign 8:N_g}{txt}{txt}{ralign 8:Var_m}{txt}{txt}{ralign 8:Var_e}{txt}{txt} {c |}
  {txt}{c LT}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 12}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 1}{c RT}
  {txt}{c |}{res}{ralign 8:.05}{res}{ralign 8:.8}{res}{ralign 8:1,000}{res}{ralign 12:250}{res}{ralign 8:.1046}{res}{ralign 8:4}{res}{ralign 8:.01095}{res}{ralign 8:1}{txt} {c |}
  {txt}{c |}{res}{ralign 8:.05}{res}{ralign 8:.9}{res}{ralign 8:1,000}{res}{ralign 12:250}{res}{ralign 8:.1193}{res}{ralign 8:4}{res}{ralign 8:.01423}{res}{ralign 8:1}{txt} {c |}
  {txt}{c |}{res}{ralign 8:.05}{res}{ralign 8:.95}{res}{ralign 8:1,000}{res}{ralign 12:250}{res}{ralign 8:.1313}{res}{ralign 8:4}{res}{ralign 8:.01724}{res}{ralign 8:1}{txt} {c |}
  {txt}{c |}{res}{ralign 8:.05}{res}{ralign 8:.99}{res}{ralign 8:1,000}{res}{ralign 12:250}{res}{ralign 8:.1537}{res}{ralign 8:4}{res}{ralign 8:.02361}{res}{ralign 8:1}{txt} {c |}
  {txt}{c BLC}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 12}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 8}{txt}{txt}{hline 1}{c BRC}

{com}. esize twosample dvotetusk if experiment2~=2 & experiment2~=3, by(ukrainetxt)

{txt}Effect size based on mean comparison

                               Obs per group:
                               ukrainetxt==0 =        249
                               ukrainetxt==1 =        250
{res}{col 1}{text}{hline 20}{c TT}{hline 12}{hline 12}{hline 12}
{col 1}{text}        Effect size{col 21}{c |}   Estimate{col 34}    [95% conf. interval]
{res}{col 1}{text}{hline 20}{c +}{hline 12}{hline 12}{hline 12}
{col 1}{text}          Cohen's {it:d}{col 21}{c |}{result}{space 2}-.2742393{col 34}{space 3}-.4504088{col 46}{space 3}-.0977964
{col 1}{text}         Hedges's {it:g}{col 21}{c |}{result}{space 2}-.2738252{col 34}{space 3}-.4497288{col 46}{space 3}-.0976487
{col 1}{text}{hline 20}{c BT}{hline 12}{hline 12}{hline 12}
{res}{txt}
{com}. 
. *Likelihood of Voting for PO/Tusk over PiS/Duda (OLS Regression)
. 
. reg dtuskbias i.experiment2 , robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}     2.74
                                                {txt}Prob > F          = {res}    0.0423
                                                {txt}R-squared         = {res}    0.0082
                                                {txt}Root MSE          =    {res} .49683

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dtuskbias{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0343775{col 41}{space 2}  .044291{col 52}{space 1}    0.78{col 61}{space 3}0.438{col 69}{space 4}-.0525368{col 82}{space 3} .1212919
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0366086{col 41}{space 2} .0442583{col 52}{space 1}    0.83{col 61}{space 3}0.408{col 69}{space 4}-.0502417{col 82}{space 3} .1234589
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1223775{col 41}{space 2} .0444185{col 52}{space 1}    2.76{col 61}{space 3}0.006{col 69}{space 4}  .035213{col 82}{space 3}  .209542
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .4056225{col 41}{space 2}  .031179{col 52}{space 1}   13.01{col 61}{space 3}0.000{col 69}{space 4} .3444383{col 82}{space 3} .4668067
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias i.experiment2 ib3.leftright3 voteeu livefree revcontactgay closega dudafav putinfav revukrainefav russiadefeat revimpreligion revimpnationality   female age education i.region i.urban i.employment, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(36, 963)        =  {res}    62.52
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.5231
                                                {txt}Root MSE          =    {res} .35038

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dtuskbias{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0332653{col 41}{space 2} .0316978{col 52}{space 1}   -1.05{col 61}{space 3}0.294{col 69}{space 4}  -.09547{col 82}{space 3} .0289394
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2}  .011681{col 41}{space 2} .0314354{col 52}{space 1}    0.37{col 61}{space 3}0.710{col 69}{space 4}-.0500087{col 82}{space 3} .0733707
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .0311407{col 41}{space 2} .0319528{col 52}{space 1}    0.97{col 61}{space 3}0.330{col 69}{space 4}-.0315644{col 82}{space 3} .0938458
{txt}{space 27} {c |}
{space 17}leftright3 {c |}
{space 25}1  {c |}{col 29}{res}{space 2} .2200621{col 41}{space 2} .0388879{col 52}{space 1}    5.66{col 61}{space 3}0.000{col 69}{space 4} .1437473{col 82}{space 3} .2963768
{txt}{space 25}2  {c |}{col 29}{res}{space 2}  .023983{col 41}{space 2} .0315872{col 52}{space 1}    0.76{col 61}{space 3}0.448{col 69}{space 4}-.0380047{col 82}{space 3} .0859708
{txt}{space 27} {c |}
{space 21}voteeu {c |}{col 29}{res}{space 2} .0992184{col 41}{space 2} .0312119{col 52}{space 1}    3.18{col 61}{space 3}0.002{col 69}{space 4} .0379672{col 82}{space 3} .1604697
{txt}{space 19}livefree {c |}{col 29}{res}{space 2} .0128352{col 41}{space 2} .0045901{col 52}{space 1}    2.80{col 61}{space 3}0.005{col 69}{space 4} .0038275{col 82}{space 3} .0218429
{txt}{space 14}revcontactgay {c |}{col 29}{res}{space 2} .0228878{col 41}{space 2} .0106829{col 52}{space 1}    2.14{col 61}{space 3}0.032{col 69}{space 4} .0019233{col 82}{space 3} .0438522
{txt}{space 19}closegay {c |}{col 29}{res}{space 2} .0129088{col 41}{space 2}  .004901{col 52}{space 1}    2.63{col 61}{space 3}0.009{col 69}{space 4}  .003291{col 82}{space 3} .0225266
{txt}{space 20}dudafav {c |}{col 29}{res}{space 2}-.0635148{col 41}{space 2} .0047525{col 52}{space 1}  -13.36{col 61}{space 3}0.000{col 69}{space 4}-.0728413{col 82}{space 3}-.0541883
{txt}{space 19}putinfav {c |}{col 29}{res}{space 2}-.0003722{col 41}{space 2} .0088645{col 52}{space 1}   -0.04{col 61}{space 3}0.967{col 69}{space 4}-.0177681{col 82}{space 3} .0170237
{txt}{space 14}revukrainefav {c |}{col 29}{res}{space 2} .0438564{col 41}{space 2} .0172488{col 52}{space 1}    2.54{col 61}{space 3}0.011{col 69}{space 4} .0100067{col 82}{space 3}  .077706
{txt}{space 15}russiadefeat {c |}{col 29}{res}{space 2} .0195593{col 41}{space 2}  .006605{col 52}{space 1}    2.96{col 61}{space 3}0.003{col 69}{space 4} .0065975{col 82}{space 3}  .032521
{txt}{space 13}revimpreligion {c |}{col 29}{res}{space 2} -.050004{col 41}{space 2} .0132552{col 52}{space 1}   -3.77{col 61}{space 3}0.000{col 69}{space 4}-.0760165{col 82}{space 3}-.0239916
{txt}{space 10}revimpnationality {c |}{col 29}{res}{space 2} .0234444{col 41}{space 2} .0182637{col 52}{space 1}    1.28{col 61}{space 3}0.200{col 69}{space 4}-.0123969{col 82}{space 3} .0592857
{txt}{space 21}female {c |}{col 29}{res}{space 2} .0225921{col 41}{space 2} .0238208{col 52}{space 1}    0.95{col 61}{space 3}0.343{col 69}{space 4}-.0241546{col 82}{space 3} .0693387
{txt}{space 24}age {c |}{col 29}{res}{space 2} .0042773{col 41}{space 2} .0010576{col 52}{space 1}    4.04{col 61}{space 3}0.000{col 69}{space 4} .0022017{col 82}{space 3} .0063528
{txt}{space 18}education {c |}{col 29}{res}{space 2} .0247838{col 41}{space 2} .0126443{col 52}{space 1}    1.96{col 61}{space 3}0.050{col 69}{space 4}-.0000298{col 82}{space 3} .0495974
{txt}{space 27} {c |}
{space 21}region {c |}
{space 5} Region 2: north-west  {c |}{col 29}{res}{space 2} .0713892{col 41}{space 2} .0385721{col 52}{space 1}    1.85{col 61}{space 3}0.065{col 69}{space 4}-.0043059{col 82}{space 3} .1470843
{txt}{space 5} Region 3: South-west  {c |}{col 29}{res}{space 2} .0711798{col 41}{space 2} .0448598{col 52}{space 1}    1.59{col 61}{space 3}0.113{col 69}{space 4}-.0168544{col 82}{space 3}  .159214
{txt}{space 10} Region 4: north  {c |}{col 29}{res}{space 2} .0667923{col 41}{space 2} .0379462{col 52}{space 1}    1.76{col 61}{space 3}0.079{col 69}{space 4}-.0076745{col 82}{space 3} .1412591
{txt}{space 8} Region 5: central  {c |}{col 29}{res}{space 2} .0505472{col 41}{space 2} .0425226{col 52}{space 1}    1.19{col 61}{space 3}0.235{col 69}{space 4}-.0329004{col 82}{space 3} .1339948
{txt}{space 8} Region 6: eastern  {c |}{col 29}{res}{space 2} .0443358{col 41}{space 2} .0389615{col 52}{space 1}    1.14{col 61}{space 3}0.255{col 69}{space 4}-.0321235{col 82}{space 3} .1207951
{txt}{space 7} Region 7: Masovian  {c |}{col 29}{res}{space 2} .0453209{col 41}{space 2}  .040285{col 52}{space 1}    1.13{col 61}{space 3}0.261{col 69}{space 4}-.0337355{col 82}{space 3} .1243773
{txt}{space 27} {c |}
{space 22}urban {c |}
 City with up to 20,000 ..  {c |}{col 29}{res}{space 2}-.0126205{col 41}{space 2} .0429365{col 52}{space 1}   -0.29{col 61}{space 3}0.769{col 69}{space 4}-.0968804{col 82}{space 3} .0716393
{txt} City between 20,000 and..  {c |}{col 29}{res}{space 2}-.0192409{col 41}{space 2} .0312589{col 52}{space 1}   -0.62{col 61}{space 3}0.538{col 69}{space 4}-.0805843{col 82}{space 3} .0421024
{txt} City with 100,000 to 50..  {c |}{col 29}{res}{space 2} .0158911{col 41}{space 2} .0329388{col 52}{space 1}    0.48{col 61}{space 3}0.630{col 69}{space 4} -.048749{col 82}{space 3} .0805313
{txt} City with more than 500..  {c |}{col 29}{res}{space 2}-.0166726{col 41}{space 2} .0405458{col 52}{space 1}   -0.41{col 61}{space 3}0.681{col 69}{space 4}-.0962409{col 82}{space 3} .0628958
{txt}{space 27} {c |}
{space 17}employment {c |}
 I have a contract of ma..  {c |}{col 29}{res}{space 2} .0020263{col 41}{space 2} .0487847{col 52}{space 1}    0.04{col 61}{space 3}0.967{col 69}{space 4}-.0937104{col 82}{space 3}  .097763
{txt} I have a contract for s..  {c |}{col 29}{res}{space 2}-.0162082{col 41}{space 2} .1015967{col 52}{space 1}   -0.16{col 61}{space 3}0.873{col 69}{space 4}-.2155848{col 82}{space 3} .1831683
{txt}{space 12} Self-employed  {c |}{col 29}{res}{space 2} .0514132{col 41}{space 2} .0647614{col 52}{space 1}    0.79{col 61}{space 3}0.427{col 69}{space 4}-.0756765{col 82}{space 3}  .178503
{txt}{space 3} Not currently employed  {c |}{col 29}{res}{space 2}-.0100889{col 41}{space 2} .0460802{col 52}{space 1}   -0.22{col 61}{space 3}0.827{col 69}{space 4}-.1005182{col 82}{space 3} .0803403
{txt} Pensioner{a:} Pensioner..  {c |}{col 29}{res}{space 2}-.0383014{col 41}{space 2} .0406586{col 52}{space 1}   -0.94{col 61}{space 3}0.346{col 69}{space 4}-.1180911{col 82}{space 3} .0414882
{txt}{space 6} {Pupil} or student}  {c |}{col 29}{res}{space 2} .0359634{col 41}{space 2} .0585674{col 52}{space 1}    0.61{col 61}{space 3}0.539{col 69}{space 4}-.0789711{col 82}{space 3} .1508979
{txt} I am involved in housek..  {c |}{col 29}{res}{space 2}-.0083602{col 41}{space 2} .0417273{col 52}{space 1}   -0.20{col 61}{space 3}0.841{col 69}{space 4}-.0902471{col 82}{space 3} .0735267
{txt}{space 20} Other  {c |}{col 29}{res}{space 2}-.0777052{col 41}{space 2} .1086467{col 52}{space 1}   -0.72{col 61}{space 3}0.475{col 69}{space 4}-.2909168{col 82}{space 3} .1355063
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-.2905828{col 41}{space 2} .1232833{col 52}{space 1}   -2.36{col 61}{space 3}0.019{col 69}{space 4}-.5325177{col 82}{space 3}-.0486478
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Likelihood of Voting for PO/Tusk over PiS/Duda (Logistic Regression)
. 
. logit dtuskbias i.experiment2 , robust

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-688.90919}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-684.80941}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-684.80912}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-684.80912}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,000}
{txt}{col 57}{lalign 13:Wald chi2({res:3})}{col 70} = {res}{ralign 6:8.16}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0429}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-684.80912}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0060}

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dtuskbias{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      z{col 61}   P>|z|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .1409297{col 41}{space 2} .1814509{col 52}{space 1}    0.78{col 61}{space 3}0.437{col 69}{space 4}-.2147076{col 82}{space 3}  .496567
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .1499795{col 41}{space 2} .1812249{col 52}{space 1}    0.83{col 61}{space 3}0.408{col 69}{space 4}-.2052147{col 82}{space 3} .5051738
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .4942091{col 41}{space 2} .1809442{col 52}{space 1}    2.73{col 61}{space 3}0.006{col 69}{space 4} .1395648{col 82}{space 3} .8488533
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-.3820918{col 41}{space 2} .1291295{col 52}{space 1}   -2.96{col 61}{space 3}0.003{col 69}{space 4}-.6351809{col 82}{space 3}-.1290026
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. logit dtuskbias i.experiment2 ib3.leftright3 voteeu livefree revcontactgay closega dudafav putinfav revukrainefav russiadefeat revimpreligion revimpnationality   female age education i.region i.urban i.employment, robust

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-688.90919}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-347.44601}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-342.75387}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-342.69658}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-342.69655}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,000}
{txt}{col 57}{lalign 13:Wald chi2({res:36})}{col 70} = {res}{ralign 6:273.44}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-342.69655}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.5026}

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dtuskbias{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      z{col 61}   P>|z|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.3357586{col 41}{space 2} .2615188{col 52}{space 1}   -1.28{col 61}{space 3}0.199{col 69}{space 4}-.8483261{col 82}{space 3} .1768088
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2}  .096299{col 41}{space 2} .2759246{col 52}{space 1}    0.35{col 61}{space 3}0.727{col 69}{space 4}-.4445034{col 82}{space 3} .6371013
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .2100932{col 41}{space 2} .2696501{col 52}{space 1}    0.78{col 61}{space 3}0.436{col 69}{space 4}-.3184113{col 82}{space 3} .7385977
{txt}{space 27} {c |}
{space 17}leftright3 {c |}
{space 25}1  {c |}{col 29}{res}{space 2} 1.566883{col 41}{space 2} .3083369{col 52}{space 1}    5.08{col 61}{space 3}0.000{col 69}{space 4} .9625542{col 82}{space 3} 2.171213
{txt}{space 25}2  {c |}{col 29}{res}{space 2} .3025312{col 41}{space 2} .2506924{col 52}{space 1}    1.21{col 61}{space 3}0.228{col 69}{space 4} -.188817{col 82}{space 3} .7938793
{txt}{space 27} {c |}
{space 21}voteeu {c |}{col 29}{res}{space 2}  1.02387{col 41}{space 2} .3042711{col 52}{space 1}    3.36{col 61}{space 3}0.001{col 69}{space 4} .4275093{col 82}{space 3}  1.62023
{txt}{space 19}livefree {c |}{col 29}{res}{space 2} .1200753{col 41}{space 2} .0434777{col 52}{space 1}    2.76{col 61}{space 3}0.006{col 69}{space 4} .0348606{col 82}{space 3}   .20529
{txt}{space 14}revcontactgay {c |}{col 29}{res}{space 2} .1834211{col 41}{space 2} .0912103{col 52}{space 1}    2.01{col 61}{space 3}0.044{col 69}{space 4} .0046522{col 82}{space 3} .3621899
{txt}{space 19}closegay {c |}{col 29}{res}{space 2} .1028733{col 41}{space 2} .0435282{col 52}{space 1}    2.36{col 61}{space 3}0.018{col 69}{space 4} .0175596{col 82}{space 3} .1881869
{txt}{space 20}dudafav {c |}{col 29}{res}{space 2} -.506236{col 41}{space 2} .0470753{col 52}{space 1}  -10.75{col 61}{space 3}0.000{col 69}{space 4}-.5985019{col 82}{space 3}-.4139702
{txt}{space 19}putinfav {c |}{col 29}{res}{space 2}  .029467{col 41}{space 2} .0824888{col 52}{space 1}    0.36{col 61}{space 3}0.721{col 69}{space 4} -.132208{col 82}{space 3} .1911421
{txt}{space 14}revukrainefav {c |}{col 29}{res}{space 2} .2878166{col 41}{space 2} .1593139{col 52}{space 1}    1.81{col 61}{space 3}0.071{col 69}{space 4}-.0244329{col 82}{space 3} .6000661
{txt}{space 15}russiadefeat {c |}{col 29}{res}{space 2}  .125694{col 41}{space 2} .0653389{col 52}{space 1}    1.92{col 61}{space 3}0.054{col 69}{space 4}-.0023679{col 82}{space 3}  .253756
{txt}{space 13}revimpreligion {c |}{col 29}{res}{space 2}-.3512043{col 41}{space 2} .1135588{col 52}{space 1}   -3.09{col 61}{space 3}0.002{col 69}{space 4}-.5737755{col 82}{space 3}-.1286332
{txt}{space 10}revimpnationality {c |}{col 29}{res}{space 2} .1840063{col 41}{space 2} .1456177{col 52}{space 1}    1.26{col 61}{space 3}0.206{col 69}{space 4}-.1013993{col 82}{space 3} .4694118
{txt}{space 21}female {c |}{col 29}{res}{space 2} .2331299{col 41}{space 2} .2062749{col 52}{space 1}    1.13{col 61}{space 3}0.258{col 69}{space 4}-.1711614{col 82}{space 3} .6374212
{txt}{space 24}age {c |}{col 29}{res}{space 2} .0279007{col 41}{space 2} .0088826{col 52}{space 1}    3.14{col 61}{space 3}0.002{col 69}{space 4}  .010491{col 82}{space 3} .0453104
{txt}{space 18}education {c |}{col 29}{res}{space 2} .2825802{col 41}{space 2} .1095104{col 52}{space 1}    2.58{col 61}{space 3}0.010{col 69}{space 4} .0679439{col 82}{space 3} .4972166
{txt}{space 27} {c |}
{space 21}region {c |}
{space 5} Region 2: north-west  {c |}{col 29}{res}{space 2} .5416888{col 41}{space 2} .3282405{col 52}{space 1}    1.65{col 61}{space 3}0.099{col 69}{space 4}-.1016508{col 82}{space 3} 1.185028
{txt}{space 5} Region 3: South-west  {c |}{col 29}{res}{space 2} .4780818{col 41}{space 2} .3808599{col 52}{space 1}    1.26{col 61}{space 3}0.209{col 69}{space 4}-.2683899{col 82}{space 3} 1.224554
{txt}{space 10} Region 4: north  {c |}{col 29}{res}{space 2} .5424591{col 41}{space 2} .3216505{col 52}{space 1}    1.69{col 61}{space 3}0.092{col 69}{space 4}-.0879643{col 82}{space 3} 1.172883
{txt}{space 8} Region 5: central  {c |}{col 29}{res}{space 2} .3326163{col 41}{space 2} .3449647{col 52}{space 1}    0.96{col 61}{space 3}0.335{col 69}{space 4}-.3435021{col 82}{space 3} 1.008735
{txt}{space 8} Region 6: eastern  {c |}{col 29}{res}{space 2} .2858399{col 41}{space 2} .3344523{col 52}{space 1}    0.85{col 61}{space 3}0.393{col 69}{space 4}-.3696747{col 82}{space 3} .9413544
{txt}{space 7} Region 7: Masovian  {c |}{col 29}{res}{space 2}  .425163{col 41}{space 2}  .378731{col 52}{space 1}    1.12{col 61}{space 3}0.262{col 69}{space 4}-.3171362{col 82}{space 3} 1.167462
{txt}{space 27} {c |}
{space 22}urban {c |}
 City with up to 20,000 ..  {c |}{col 29}{res}{space 2}  .120578{col 41}{space 2} .3895925{col 52}{space 1}    0.31{col 61}{space 3}0.757{col 69}{space 4}-.6430093{col 82}{space 3} .8841654
{txt} City between 20,000 and..  {c |}{col 29}{res}{space 2}-.1352463{col 41}{space 2} .2557718{col 52}{space 1}   -0.53{col 61}{space 3}0.597{col 69}{space 4}-.6365498{col 82}{space 3} .3660572
{txt} City with 100,000 to 50..  {c |}{col 29}{res}{space 2} .0773013{col 41}{space 2} .2904413{col 52}{space 1}    0.27{col 61}{space 3}0.790{col 69}{space 4}-.4919532{col 82}{space 3} .6465558
{txt} City with more than 500..  {c |}{col 29}{res}{space 2}-.0764651{col 41}{space 2} .3337948{col 52}{space 1}   -0.23{col 61}{space 3}0.819{col 69}{space 4}-.7306909{col 82}{space 3} .5777606
{txt}{space 27} {c |}
{space 17}employment {c |}
 I have a contract of ma..  {c |}{col 29}{res}{space 2} .0305851{col 41}{space 2} .4159109{col 52}{space 1}    0.07{col 61}{space 3}0.941{col 69}{space 4}-.7845853{col 82}{space 3} .8457555
{txt} I have a contract for s..  {c |}{col 29}{res}{space 2}-.0496049{col 41}{space 2} .9776361{col 52}{space 1}   -0.05{col 61}{space 3}0.960{col 69}{space 4}-1.965736{col 82}{space 3} 1.866527
{txt}{space 12} Self-employed  {c |}{col 29}{res}{space 2}  .210064{col 41}{space 2} .5222028{col 52}{space 1}    0.40{col 61}{space 3}0.687{col 69}{space 4}-.8134348{col 82}{space 3} 1.233563
{txt}{space 3} Not currently employed  {c |}{col 29}{res}{space 2}-.1933433{col 41}{space 2} .4254669{col 52}{space 1}   -0.45{col 61}{space 3}0.650{col 69}{space 4}-1.027243{col 82}{space 3} .6405565
{txt} Pensioner{a:} Pensioner..  {c |}{col 29}{res}{space 2}-.2274591{col 41}{space 2} .3660733{col 52}{space 1}   -0.62{col 61}{space 3}0.534{col 69}{space 4}-.9449495{col 82}{space 3} .4900314
{txt}{space 6} {Pupil} or student}  {c |}{col 29}{res}{space 2} .2251893{col 41}{space 2} .4833113{col 52}{space 1}    0.47{col 61}{space 3}0.641{col 69}{space 4}-.7220833{col 82}{space 3} 1.172462
{txt} I am involved in housek..  {c |}{col 29}{res}{space 2}-.1119891{col 41}{space 2} .3684427{col 52}{space 1}   -0.30{col 61}{space 3}0.761{col 69}{space 4}-.8341234{col 82}{space 3} .6101453
{txt}{space 20} Other  {c |}{col 29}{res}{space 2}-1.242296{col 41}{space 2} 1.179108{col 52}{space 1}   -1.05{col 61}{space 3}0.292{col 69}{space 4}-3.553306{col 82}{space 3} 1.068714
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-6.614041{col 41}{space 2} 1.134894{col 52}{space 1}   -5.83{col 61}{space 3}0.000{col 69}{space 4}-8.838391{col 82}{space 3} -4.38969
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Accounting for Duda+Putin+Ukraine Treatment Effects (OLS Regression)
. 
. reg dtuskbias ukrainetxt , robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(1, 998)         =  {res}     7.34
                                                {txt}Prob > F          = {res}    0.0069
                                                {txt}R-squared         = {res}    0.0074
                                                {txt}Root MSE          =    {res} .49654

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dtuskbias{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2} .0986667{col 26}{space 2} .0364169{col 37}{space 1}    2.71{col 46}{space 3}0.007{col 54}{space 4} .0272042{col 67}{space 3} .1701292
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4293333{col 26}{space 2} .0180923{col 37}{space 1}   23.73{col 46}{space 3}0.000{col 54}{space 4} .3938301{col 67}{space 3} .4648366
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##ib3.leftright3 , robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(5, 994)         =  {res}    84.71
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2459
                                                {txt}Root MSE          =    {res} .43365

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}            dtuskbias{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      t{col 55}   P>|t|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.ukrainetxt {c |}{col 23}{res}{space 2} .1016224{col 35}{space 2} .0568191{col 46}{space 1}    1.79{col 55}{space 3}0.074{col 63}{space 4}-.0098767{col 76}{space 3} .2131215
{txt}{space 21} {c |}
{space 11}leftright3 {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .6331013{col 35}{space 2} .0373606{col 46}{space 1}   16.95{col 55}{space 3}0.000{col 63}{space 4} .5597865{col 76}{space 3}  .706416
{txt}{space 19}2  {c |}{col 23}{res}{space 2} .2602418{col 35}{space 2} .0364085{col 46}{space 1}    7.15{col 55}{space 3}0.000{col 63}{space 4} .1887954{col 76}{space 3} .3316882
{txt}{space 21} {c |}
ukrainetxt#leftright3 {c |}
{space 17}1 1  {c |}{col 23}{res}{space 2}-.0343497{col 35}{space 2} .0742747{col 46}{space 1}   -0.46{col 55}{space 3}0.644{col 63}{space 4}-.1801029{col 76}{space 3} .1114036
{txt}{space 17}1 2  {c |}{col 23}{res}{space 2}-.0851915{col 35}{space 2} .0819425{col 46}{space 1}   -1.04{col 55}{space 3}0.299{col 63}{space 4}-.2459916{col 76}{space 3} .0756085
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} .1518987{col 35}{space 2} .0233848{col 46}{space 1}    6.50{col 55}{space 3}0.000{col 63}{space 4} .1060095{col 76}{space 3}  .197788
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.livefree, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}   120.16
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2003
                                                {txt}Root MSE          =    {res} .44612

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}            dtuskbias{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      t{col 55}   P>|t|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.ukrainetxt {c |}{col 23}{res}{space 2} .0433357{col 35}{space 2} .0686038{col 46}{space 1}    0.63{col 55}{space 3}0.528{col 63}{space 4}-.0912889{col 76}{space 3} .1779604
{txt}{space 13}livefree {c |}{col 23}{res}{space 2} .0697457{col 35}{space 2} .0043836{col 46}{space 1}   15.91{col 55}{space 3}0.000{col 63}{space 4} .0611437{col 76}{space 3} .0783478
{txt}{space 21} {c |}
ukrainetxt#c.livefree {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .0049008{col 35}{space 2} .0089682{col 46}{space 1}    0.55{col 55}{space 3}0.585{col 63}{space 4}-.0126979{col 76}{space 3} .0224996
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2}-.0790666{col 35}{space 2} .0313393{col 46}{space 1}   -2.52{col 55}{space 3}0.012{col 63}{space 4}-.1405653{col 76}{space 3} -.017568
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.dudafav, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}   297.50
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.3660
                                                {txt}Root MSE          =    {res} .39722

{txt}{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           dtuskbias{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}1.ukrainetxt {c |}{col 22}{res}{space 2} .0987516{col 34}{space 2} .0438869{col 45}{space 1}    2.25{col 54}{space 3}0.025{col 62}{space 4} .0126301{col 75}{space 3}  .184873
{txt}{space 13}dudafav {c |}{col 22}{res}{space 2}-.0896194{col 34}{space 2} .0036912{col 45}{space 1}  -24.28{col 54}{space 3}0.000{col 62}{space 4}-.0968629{col 75}{space 3}-.0823759
{txt}{space 20} {c |}
ukrainetxt#c.dudafav {c |}
{space 18}1  {c |}{col 22}{res}{space 2}-.0092212{col 34}{space 2} .0068529{col 45}{space 1}   -1.35{col 54}{space 3}0.179{col 62}{space 4} -.022669{col 75}{space 3} .0042266
{txt}{space 20} {c |}
{space 15}_cons {c |}{col 22}{res}{space 2} .7759813{col 34}{space 2}  .023744{col 45}{space 1}   32.68{col 54}{space 3}0.000{col 62}{space 4} .7293872{col 75}{space 3} .8225753
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.putinfav, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}    15.16
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0340
                                                {txt}Root MSE          =    {res} .49032

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}            dtuskbias{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      t{col 55}   P>|t|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.ukrainetxt {c |}{col 23}{res}{space 2} .1003702{col 35}{space 2} .0394851{col 46}{space 1}    2.54{col 55}{space 3}0.011{col 63}{space 4} .0228866{col 76}{space 3} .1778538
{txt}{space 13}putinfav {c |}{col 23}{res}{space 2}-.0437635{col 35}{space 2} .0081444{col 46}{space 1}   -5.37{col 55}{space 3}0.000{col 63}{space 4}-.0597456{col 76}{space 3}-.0277814
{txt}{space 21} {c |}
ukrainetxt#c.putinfav {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.0053484{col 35}{space 2}  .020001{col 46}{space 1}   -0.27{col 55}{space 3}0.789{col 63}{space 4}-.0445974{col 76}{space 3} .0339005
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} .4641691{col 35}{space 2} .0197764{col 46}{space 1}   23.47{col 55}{space 3}0.000{col 63}{space 4} .4253609{col 76}{space 3} .5029773
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.revukrainefav, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}     8.62
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0232
                                                {txt}Root MSE          =    {res} .49306

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                 dtuskbias{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      t{col 60}   P>|t|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}1.ukrainetxt {c |}{col 28}{res}{space 2} .2206494{col 40}{space 2} .1219698{col 51}{space 1}    1.81{col 60}{space 3}0.071{col 68}{space 4}-.0186978{col 81}{space 3} .4599967
{txt}{space 13}revukrainefav {c |}{col 28}{res}{space 2} .0878187{col 40}{space 2} .0216785{col 51}{space 1}    4.05{col 60}{space 3}0.000{col 68}{space 4}  .045278{col 81}{space 3} .1303594
{txt}{space 26} {c |}
ukrainetxt#c.revukrainefav {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0445315{col 40}{space 2} .0448671{col 51}{space 1}   -0.99{col 60}{space 3}0.321{col 68}{space 4}-.1325765{col 81}{space 3} .0435135
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .1951501{col 40}{space 2} .0592294{col 51}{space 1}    3.29{col 60}{space 3}0.001{col 68}{space 4} .0789214{col 81}{space 3} .3113789
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.revcontactgay, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}    34.23
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0855
                                                {txt}Root MSE          =    {res} .47708

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                 dtuskbias{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      t{col 60}   P>|t|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}1.ukrainetxt {c |}{col 28}{res}{space 2} .1592502{col 40}{space 2} .0833914{col 51}{space 1}    1.91{col 60}{space 3}0.056{col 68}{space 4}-.0043929{col 81}{space 3} .3228933
{txt}{space 13}revcontactgay {c |}{col 28}{res}{space 2} .1150576{col 40}{space 2} .0131079{col 51}{space 1}    8.78{col 60}{space 3}0.000{col 68}{space 4} .0893354{col 81}{space 3} .1407798
{txt}{space 26} {c |}
ukrainetxt#c.revcontactgay {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0252804{col 40}{space 2} .0260956{col 51}{space 1}   -0.97{col 60}{space 3}0.333{col 68}{space 4} -.076489{col 81}{space 3} .0259282
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .1094732{col 40}{space 2} .0396997{col 51}{space 1}    2.76{col 60}{space 3}0.006{col 68}{space 4} .0315685{col 81}{space 3} .1873779
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.closegay, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}    84.19
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1746
                                                {txt}Root MSE          =    {res} .45324

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}            dtuskbias{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      t{col 55}   P>|t|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.ukrainetxt {c |}{col 23}{res}{space 2} .0287866{col 35}{space 2} .0464547{col 46}{space 1}    0.62{col 55}{space 3}0.536{col 63}{space 4}-.0623738{col 76}{space 3}  .119947
{txt}{space 13}closegay {c |}{col 23}{res}{space 2} .0616226{col 35}{space 2} .0050084{col 46}{space 1}   12.30{col 55}{space 3}0.000{col 63}{space 4} .0517943{col 76}{space 3} .0714509
{txt}{space 21} {c |}
ukrainetxt#c.closegay {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .0118081{col 35}{space 2} .0093528{col 46}{space 1}    1.26{col 55}{space 3}0.207{col 63}{space 4}-.0065454{col 76}{space 3} .0301617
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} .2363314{col 35}{space 2} .0221424{col 46}{space 1}   10.67{col 55}{space 3}0.000{col 63}{space 4} .1928804{col 76}{space 3} .2797824
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.supportrights, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}   195.30
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2871
                                                {txt}Root MSE          =    {res} .42121

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                 dtuskbias{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      t{col 60}   P>|t|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}1.ukrainetxt {c |}{col 28}{res}{space 2} .0953205{col 40}{space 2}   .05541{col 51}{space 1}    1.72{col 60}{space 3}0.086{col 68}{space 4}-.0134133{col 81}{space 3} .2040542
{txt}{space 13}supportrights {c |}{col 28}{res}{space 2}  .079319{col 40}{space 2} .0038322{col 51}{space 1}   20.70{col 60}{space 3}0.000{col 68}{space 4} .0717988{col 81}{space 3} .0868392
{txt}{space 26} {c |}
ukrainetxt#c.supportrights {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0019827{col 40}{space 2}  .007993{col 51}{space 1}   -0.25{col 60}{space 3}0.804{col 68}{space 4}-.0176677{col 81}{space 3} .0137023
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2}-.0266982{col 40}{space 2}  .023434{col 51}{space 1}   -1.14{col 60}{space 3}0.255{col 68}{space 4}-.0726838{col 81}{space 3} .0192874
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dtuskbias ukrainetxt##c.russiadefeat, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}    16.37
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0383
                                                {txt}Root MSE          =    {res} .48924

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 27}{c |}{col 39}    Robust
{col 1}                dtuskbias{col 27}{c |} Coefficient{col 39}  std. err.{col 51}      t{col 59}   P>|t|{col 67}     [95% con{col 80}f. interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}1.ukrainetxt {c |}{col 27}{res}{space 2}-.0456856{col 39}{space 2} .1313166{col 50}{space 1}   -0.35{col 59}{space 3}0.728{col 67}{space 4}-.3033745{col 80}{space 3} .2120033
{txt}{space 13}russiadefeat {c |}{col 27}{res}{space 2} .0331338{col 39}{space 2} .0063987{col 50}{space 1}    5.18{col 59}{space 3}0.000{col 67}{space 4} .0205774{col 80}{space 3} .0456903
{txt}{space 25} {c |}
ukrainetxt#c.russiadefeat {c |}
{space 23}1  {c |}{col 27}{res}{space 2} .0158202{col 39}{space 2} .0145745{col 50}{space 1}    1.09{col 59}{space 3}0.278{col 67}{space 4}-.0127801{col 80}{space 3} .0444205
{txt}{space 25} {c |}
{space 20}_cons {c |}{col 27}{res}{space 2} .1391693{col 39}{space 2}  .056766{col 50}{space 1}    2.45{col 59}{space 3}0.014{col 67}{space 4} .0277747{col 80}{space 3} .2505639
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Relationship between Left-Right Ideology and LGBT+ Attitudes (OLS Regression)
. 
. reg livefree leftright  female age education i.region i.urban i.employment  revimpreligion revimpnationality   revrussiafav revukrainefav , robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(26, 973)        =  {res}     8.48
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1797
                                                {txt}Root MSE          =    {res} 2.8325

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                   livefree{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}leftright {c |}{col 29}{res}{space 2}-.2980654{col 41}{space 2} .0543721{col 52}{space 1}   -5.48{col 61}{space 3}0.000{col 69}{space 4}-.4047655{col 82}{space 3}-.1913653
{txt}{space 21}female {c |}{col 29}{res}{space 2} .5521311{col 41}{space 2} .1880594{col 52}{space 1}    2.94{col 61}{space 3}0.003{col 69}{space 4} .1830824{col 82}{space 3} .9211797
{txt}{space 24}age {c |}{col 29}{res}{space 2} .0021922{col 41}{space 2} .0088276{col 52}{space 1}    0.25{col 61}{space 3}0.804{col 69}{space 4}-.0151311{col 82}{space 3} .0195156
{txt}{space 18}education {c |}{col 29}{res}{space 2} .1825259{col 41}{space 2} .1108705{col 52}{space 1}    1.65{col 61}{space 3}0.100{col 69}{space 4} -.035047{col 82}{space 3} .4000988
{txt}{space 27} {c |}
{space 21}region {c |}
{space 5} Region 2: north-west  {c |}{col 29}{res}{space 2} .2684347{col 41}{space 2} .2843018{col 52}{space 1}    0.94{col 61}{space 3}0.345{col 69}{space 4}-.2894806{col 82}{space 3} .8263501
{txt}{space 5} Region 3: South-west  {c |}{col 29}{res}{space 2} .4315374{col 41}{space 2}  .338959{col 52}{space 1}    1.27{col 61}{space 3}0.203{col 69}{space 4}-.2336374{col 82}{space 3} 1.096712
{txt}{space 10} Region 4: north  {c |}{col 29}{res}{space 2} .2175015{col 41}{space 2} .3278217{col 52}{space 1}    0.66{col 61}{space 3}0.507{col 69}{space 4}-.4258174{col 82}{space 3} .8608204
{txt}{space 8} Region 5: central  {c |}{col 29}{res}{space 2} .4013398{col 41}{space 2} .3252764{col 52}{space 1}    1.23{col 61}{space 3}0.218{col 69}{space 4}-.2369843{col 82}{space 3} 1.039664
{txt}{space 8} Region 6: eastern  {c |}{col 29}{res}{space 2} .3474532{col 41}{space 2} .3331959{col 52}{space 1}    1.04{col 61}{space 3}0.297{col 69}{space 4}-.3064122{col 82}{space 3} 1.001318
{txt}{space 7} Region 7: Masovian  {c |}{col 29}{res}{space 2}-.2824555{col 41}{space 2}  .314795{col 52}{space 1}   -0.90{col 61}{space 3}0.370{col 69}{space 4}-.9002107{col 82}{space 3} .3352998
{txt}{space 27} {c |}
{space 22}urban {c |}
 City with up to 20,000 ..  {c |}{col 29}{res}{space 2}-.0967869{col 41}{space 2} .3423523{col 52}{space 1}   -0.28{col 61}{space 3}0.777{col 69}{space 4}-.7686208{col 82}{space 3} .5750471
{txt} City between 20,000 and..  {c |}{col 29}{res}{space 2} .0629288{col 41}{space 2} .2375203{col 52}{space 1}    0.26{col 61}{space 3}0.791{col 69}{space 4}-.4031821{col 82}{space 3} .5290398
{txt} City with 100,000 to 50..  {c |}{col 29}{res}{space 2}  .179502{col 41}{space 2}  .272146{col 52}{space 1}    0.66{col 61}{space 3}0.510{col 69}{space 4}-.3545586{col 82}{space 3} .7135626
{txt} City with more than 500..  {c |}{col 29}{res}{space 2} .3560479{col 41}{space 2} .2870038{col 52}{space 1}    1.24{col 61}{space 3}0.215{col 69}{space 4}-.2071698{col 82}{space 3} .9192656
{txt}{space 27} {c |}
{space 17}employment {c |}
 I have a contract of ma..  {c |}{col 29}{res}{space 2} -.269908{col 41}{space 2} .3548922{col 52}{space 1}   -0.76{col 61}{space 3}0.447{col 69}{space 4}-.9663503{col 82}{space 3} .4265342
{txt} I have a contract for s..  {c |}{col 29}{res}{space 2} .5981817{col 41}{space 2} .7582274{col 52}{space 1}    0.79{col 61}{space 3}0.430{col 69}{space 4}-.8897676{col 82}{space 3} 2.086131
{txt}{space 12} Self-employed  {c |}{col 29}{res}{space 2} 1.064615{col 41}{space 2} .4033083{col 52}{space 1}    2.64{col 61}{space 3}0.008{col 69}{space 4} .2731605{col 82}{space 3} 1.856069
{txt}{space 3} Not currently employed  {c |}{col 29}{res}{space 2}-.5184358{col 41}{space 2} .4000863{col 52}{space 1}   -1.30{col 61}{space 3}0.195{col 69}{space 4}-1.303567{col 82}{space 3} .2666955
{txt} Pensioner{a:} Pensioner..  {c |}{col 29}{res}{space 2} .4318149{col 41}{space 2} .3359677{col 52}{space 1}    1.29{col 61}{space 3}0.199{col 69}{space 4}-.2274898{col 82}{space 3}  1.09112
{txt}{space 6} {Pupil} or student}  {c |}{col 29}{res}{space 2} .4643895{col 41}{space 2} .3931992{col 52}{space 1}    1.18{col 61}{space 3}0.238{col 69}{space 4}-.3072265{col 82}{space 3} 1.236005
{txt} I am involved in housek..  {c |}{col 29}{res}{space 2}-.5032862{col 41}{space 2} .4140592{col 52}{space 1}   -1.22{col 61}{space 3}0.224{col 69}{space 4}-1.315838{col 82}{space 3} .3092656
{txt}{space 20} Other  {c |}{col 29}{res}{space 2}-.1010587{col 41}{space 2} .8868788{col 52}{space 1}   -0.11{col 61}{space 3}0.909{col 69}{space 4}-1.841474{col 82}{space 3} 1.639357
{txt}{space 27} {c |}
{space 13}revimpreligion {c |}{col 29}{res}{space 2}-.5420186{col 41}{space 2} .1094133{col 52}{space 1}   -4.95{col 61}{space 3}0.000{col 69}{space 4}-.7567319{col 82}{space 3}-.3273053
{txt}{space 10}revimpnationality {c |}{col 29}{res}{space 2}-.1394952{col 41}{space 2} .1407944{col 52}{space 1}   -0.99{col 61}{space 3}0.322{col 69}{space 4}-.4157909{col 82}{space 3} .1368004
{txt}{space 15}revrussiafav {c |}{col 29}{res}{space 2}-.3149764{col 41}{space 2} .1907722{col 52}{space 1}   -1.65{col 61}{space 3}0.099{col 69}{space 4}-.6893488{col 82}{space 3}  .059396
{txt}{space 14}revukrainefav {c |}{col 29}{res}{space 2} .3567769{col 41}{space 2} .1411745{col 52}{space 1}    2.53{col 61}{space 3}0.012{col 69}{space 4} .0797352{col 82}{space 3} .6338185
{txt}{space 22}_cons {c |}{col 29}{res}{space 2} 9.078214{col 41}{space 2} .8176456{col 52}{space 1}   11.10{col 61}{space 3}0.000{col 69}{space 4} 7.473663{col 82}{space 3} 10.68277
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Likelihood of Party Votes by Treatment Groups and LGBTIQ Tolerance
. 
. logit dvotetusk i.experiment2##c.livefree, robust

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-671.35644}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-598.25318}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-595.78856}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-595.77922}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-595.77922}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,000}
{txt}{col 57}{lalign 13:Wald chi2({res:7})}{col 70} = {res}{ralign 6:109.73}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-595.77922}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.1126}

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvotetusk{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      z{col 61}   P>|z|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}  .578872{col 41}{space 2} .7694172{col 52}{space 1}    0.75{col 61}{space 3}0.452{col 69}{space 4} -.929158{col 82}{space 3} 2.086902
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .7064096{col 41}{space 2} .7307168{col 52}{space 1}    0.97{col 61}{space 3}0.334{col 69}{space 4} -.725769{col 82}{space 3} 2.138588
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} 1.408621{col 41}{space 2} .7143917{col 52}{space 1}    1.97{col 61}{space 3}0.049{col 69}{space 4} .0084386{col 82}{space 3} 2.808803
{txt}{space 27} {c |}
{space 19}livefree {c |}{col 29}{res}{space 2} .3681485{col 41}{space 2} .0642831{col 52}{space 1}    5.73{col 61}{space 3}0.000{col 69}{space 4} .2421559{col 82}{space 3}  .494141
{txt}{space 27} {c |}
{space 5}experiment2#c.livefree {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0808335{col 41}{space 2} .0889284{col 52}{space 1}   -0.91{col 61}{space 3}0.363{col 69}{space 4}-.2551299{col 82}{space 3} .0934629
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2}-.0842504{col 41}{space 2} .0857107{col 52}{space 1}   -0.98{col 61}{space 3}0.326{col 69}{space 4}-.2522404{col 82}{space 3} .0837395
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.1114503{col 41}{space 2} .0842872{col 52}{space 1}   -1.32{col 61}{space 3}0.186{col 69}{space 4}-.2766502{col 82}{space 3} .0537497
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-3.422444{col 41}{space 2} .5509329{col 52}{space 1}   -6.21{col 61}{space 3}0.000{col 69}{space 4}-4.502252{col 82}{space 3}-2.342635
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. logit dvoteduda i.experiment2##c.livefree, robust

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-597.61384}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-524.52059}  
Iteration 2:{space 2}Log pseudolikelihood = {res: -523.3431}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-523.34224}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-523.34224}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,000}
{txt}{col 57}{lalign 13:Wald chi2({res:7})}{col 70} = {res}{ralign 6:123.18}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-523.34224}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.1243}

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      z{col 61}   P>|z|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .2604286{col 41}{space 2}  .498135{col 52}{space 1}    0.52{col 61}{space 3}0.601{col 69}{space 4}-.7158981{col 82}{space 3} 1.236755
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .9976628{col 41}{space 2} .5289037{col 52}{space 1}    1.89{col 61}{space 3}0.059{col 69}{space 4}-.0389693{col 82}{space 3} 2.034295
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .6745885{col 41}{space 2} .5360666{col 52}{space 1}    1.26{col 61}{space 3}0.208{col 69}{space 4}-.3760828{col 82}{space 3}  1.72526
{txt}{space 27} {c |}
{space 19}livefree {c |}{col 29}{res}{space 2}-.2225315{col 41}{space 2} .0467984{col 52}{space 1}   -4.76{col 61}{space 3}0.000{col 69}{space 4}-.3142547{col 82}{space 3}-.1308084
{txt}{space 27} {c |}
{space 5}experiment2#c.livefree {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} -.032756{col 41}{space 2} .0663515{col 52}{space 1}   -0.49{col 61}{space 3}0.622{col 69}{space 4}-.1628026{col 82}{space 3} .0972906
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} -.105229{col 41}{space 2} .0709574{col 52}{space 1}   -1.48{col 61}{space 3}0.138{col 69}{space 4}-.2443029{col 82}{space 3}  .033845
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.0813871{col 41}{space 2} .0711751{col 52}{space 1}   -1.14{col 61}{space 3}0.253{col 69}{space 4}-.2208878{col 82}{space 3} .0581136
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .5277187{col 41}{space 2} .3414551{col 52}{space 1}    1.55{col 61}{space 3}0.122{col 69}{space 4} -.141521{col 82}{space 3} 1.196958
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Figure – Treatment Effects Moderated by Pre-Txt LGBT+ Rights Support
. 
. reg dvotetusk i.experiment2##c.livefree, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(7, 992)         =  {res}    33.09
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1314
                                                {txt}Root MSE          =    {res} .45764

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvotetusk{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0701992{col 41}{space 2} .0695562{col 52}{space 1}    1.01{col 61}{space 3}0.313{col 69}{space 4}-.0662949{col 82}{space 3} .2066933
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0652544{col 41}{space 2}  .071711{col 52}{space 1}    0.91{col 61}{space 3}0.363{col 69}{space 4}-.0754682{col 82}{space 3}  .205977
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1547517{col 41}{space 2} .0833241{col 52}{space 1}    1.86{col 61}{space 3}0.064{col 69}{space 4}-.0087601{col 82}{space 3} .3182635
{txt}{space 27} {c |}
{space 19}livefree {c |}{col 29}{res}{space 2}  .061098{col 41}{space 2}  .007367{col 52}{space 1}    8.29{col 61}{space 3}0.000{col 69}{space 4} .0466413{col 82}{space 3} .0755547
{txt}{space 27} {c |}
{space 5}experiment2#c.livefree {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0116127{col 41}{space 2} .0103232{col 52}{space 1}   -1.12{col 61}{space 3}0.261{col 69}{space 4}-.0318706{col 82}{space 3} .0086452
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} -.008748{col 41}{space 2} .0106579{col 52}{space 1}   -0.82{col 61}{space 3}0.412{col 69}{space 4}-.0296626{col 82}{space 3} .0121666
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.0063259{col 41}{space 2} .0114634{col 52}{space 1}   -0.55{col 61}{space 3}0.581{col 69}{space 4}-.0288211{col 82}{space 3} .0161693
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-.0763908{col 41}{space 2} .0476312{col 52}{space 1}   -1.60{col 61}{space 3}0.109{col 69}{space 4}-.1698604{col 82}{space 3} .0170787
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mcp  livefree experiment2, at2(1 2 3 4)
{res}{txt}
{com}. 
. *Relationship between Age and PiS/PO Voting
. 
. reg dvotetusk i.experiment2 c.age, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(4, 995)         =  {res}     4.90
                                                {txt}Prob > F          = {res}    0.0006
                                                {txt}R-squared         = {res}    0.0195
                                                {txt}Root MSE          =    {res} .48549

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvotetusk{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0026435{col 41}{space 2} .0429531{col 52}{space 1}    0.06{col 61}{space 3}0.951{col 69}{space 4}-.0816456{col 82}{space 3} .0869326
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0139522{col 41}{space 2} .0429953{col 52}{space 1}    0.32{col 61}{space 3}0.746{col 69}{space 4}-.0704196{col 82}{space 3} .0983241
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1323303{col 41}{space 2} .0438091{col 52}{space 1}    3.02{col 61}{space 3}0.003{col 69}{space 4} .0463615{col 82}{space 3} .2182992
{txt}{space 27} {c |}
{space 24}age {c |}{col 29}{res}{space 2} .0029809{col 41}{space 2} .0011589{col 52}{space 1}    2.57{col 61}{space 3}0.010{col 69}{space 4} .0007067{col 82}{space 3}  .005255
{txt}{space 22}_cons {c |}{col 29}{res}{space 2} .2377756{col 41}{space 2} .0549335{col 52}{space 1}    4.33{col 61}{space 3}0.000{col 69}{space 4} .1299768{col 82}{space 3} .3455744
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvoteduda i.experiment2 c.age, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(4, 995)         =  {res}     2.62
                                                {txt}Prob > F          = {res}    0.0336
                                                {txt}R-squared         = {res}    0.0103
                                                {txt}Root MSE          =    {res} .45021

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0050294{col 41}{space 2} .0397554{col 52}{space 1}   -0.13{col 61}{space 3}0.899{col 69}{space 4}-.0830434{col 82}{space 3} .0729846
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0342639{col 41}{space 2} .0404004{col 52}{space 1}    0.85{col 61}{space 3}0.397{col 69}{space 4}-.0450158{col 82}{space 3} .1135436
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.0035269{col 41}{space 2} .0400024{col 52}{space 1}   -0.09{col 61}{space 3}0.930{col 69}{space 4}-.0820256{col 82}{space 3} .0749719
{txt}{space 27} {c |}
{space 24}age {c |}{col 29}{res}{space 2} .0032184{col 41}{space 2} .0010576{col 52}{space 1}    3.04{col 61}{space 3}0.002{col 69}{space 4}  .001143{col 82}{space 3} .0052938
{txt}{space 22}_cons {c |}{col 29}{res}{space 2} .1479186{col 41}{space 2} .0478847{col 52}{space 1}    3.09{col 61}{space 3}0.002{col 69}{space 4}  .053952{col 82}{space 3} .2418851
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg dvotetusk i.experiment2##c.age, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(7, 992)         =  {res}     2.85
                                                {txt}Prob > F          = {res}    0.0061
                                                {txt}R-squared         = {res}    0.0200
                                                {txt}Root MSE          =    {res} .48609

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvotetusk{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .0750825{col 41}{space 2} .1349695{col 52}{space 1}    0.56{col 61}{space 3}0.578{col 69}{space 4} -.189776{col 82}{space 3}  .339941
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2}-.0042745{col 41}{space 2} .1397049{col 52}{space 1}   -0.03{col 61}{space 3}0.976{col 69}{space 4}-.2784256{col 82}{space 3} .2698766
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .1457617{col 41}{space 2} .1434143{col 52}{space 1}    1.02{col 61}{space 3}0.310{col 69}{space 4}-.1356686{col 82}{space 3}  .427192
{txt}{space 27} {c |}
{space 24}age {c |}{col 29}{res}{space 2} .0034169{col 41}{space 2} .0023889{col 52}{space 1}    1.43{col 61}{space 3}0.153{col 69}{space 4} -.001271{col 82}{space 3} .0081047
{txt}{space 27} {c |}
{space 10}experiment2#c.age {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0018055{col 41}{space 2} .0032345{col 52}{space 1}   -0.56{col 61}{space 3}0.577{col 69}{space 4}-.0081528{col 82}{space 3} .0045419
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0004315{col 41}{space 2} .0033155{col 52}{space 1}    0.13{col 61}{space 3}0.896{col 69}{space 4}-.0060747{col 82}{space 3} .0069376
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}-.0003365{col 41}{space 2} .0034015{col 52}{space 1}   -0.10{col 61}{space 3}0.921{col 69}{space 4}-.0070115{col 82}{space 3} .0063385
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .2202752{col 41}{space 2} .0992412{col 52}{space 1}    2.22{col 61}{space 3}0.027{col 69}{space 4} .0255285{col 82}{space 3}  .415022
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvoteduda i.experiment2##c.age, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(7, 992)         =  {res}     3.53
                                                {txt}Prob > F          = {res}    0.0009
                                                {txt}R-squared         = {res}    0.0205
                                                {txt}Root MSE          =    {res} .44857

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .2918456{col 41}{space 2} .1219053{col 52}{space 1}    2.39{col 61}{space 3}0.017{col 69}{space 4} .0526237{col 82}{space 3} .5310675
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .1594428{col 41}{space 2}  .112552{col 52}{space 1}    1.42{col 61}{space 3}0.157{col 69}{space 4}-.0614245{col 82}{space 3} .3803101
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .3543003{col 41}{space 2} .1200545{col 52}{space 1}    2.95{col 61}{space 3}0.003{col 69}{space 4} .1187103{col 82}{space 3} .5898903
{txt}{space 27} {c |}
{space 24}age {c |}{col 29}{res}{space 2} .0080884{col 41}{space 2} .0020079{col 52}{space 1}    4.03{col 61}{space 3}0.000{col 69}{space 4}  .004148{col 82}{space 3} .0120287
{txt}{space 27} {c |}
{space 10}experiment2#c.age {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0073974{col 41}{space 2} .0030161{col 52}{space 1}   -2.45{col 61}{space 3}0.014{col 69}{space 4}-.0133161{col 82}{space 3}-.0014787
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} -.003163{col 41}{space 2} .0028249{col 52}{space 1}   -1.12{col 61}{space 3}0.263{col 69}{space 4}-.0087065{col 82}{space 3} .0023804
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}  -.00884{col 41}{space 2}  .002918{col 52}{space 1}   -3.03{col 61}{space 3}0.003{col 69}{space 4}-.0145663{col 82}{space 3}-.0031138
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-.0475627{col 41}{space 2} .0773661{col 52}{space 1}   -0.61{col 61}{space 3}0.539{col 69}{space 4}-.1993827{col 82}{space 3} .1042574
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg dvoteduda i.experiment2##c.age, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(7, 992)         =  {res}     3.53
                                                {txt}Prob > F          = {res}    0.0009
                                                {txt}R-squared         = {res}    0.0205
                                                {txt}Root MSE          =    {res} .44857

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .2918456{col 41}{space 2} .1219053{col 52}{space 1}    2.39{col 61}{space 3}0.017{col 69}{space 4} .0526237{col 82}{space 3} .5310675
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .1594428{col 41}{space 2}  .112552{col 52}{space 1}    1.42{col 61}{space 3}0.157{col 69}{space 4}-.0614245{col 82}{space 3} .3803101
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .3543003{col 41}{space 2} .1200545{col 52}{space 1}    2.95{col 61}{space 3}0.003{col 69}{space 4} .1187103{col 82}{space 3} .5898903
{txt}{space 27} {c |}
{space 24}age {c |}{col 29}{res}{space 2} .0080884{col 41}{space 2} .0020079{col 52}{space 1}    4.03{col 61}{space 3}0.000{col 69}{space 4}  .004148{col 82}{space 3} .0120287
{txt}{space 27} {c |}
{space 10}experiment2#c.age {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2}-.0073974{col 41}{space 2} .0030161{col 52}{space 1}   -2.45{col 61}{space 3}0.014{col 69}{space 4}-.0133161{col 82}{space 3}-.0014787
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} -.003163{col 41}{space 2} .0028249{col 52}{space 1}   -1.12{col 61}{space 3}0.263{col 69}{space 4}-.0087065{col 82}{space 3} .0023804
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}  -.00884{col 41}{space 2}  .002918{col 52}{space 1}   -3.03{col 61}{space 3}0.003{col 69}{space 4}-.0145663{col 82}{space 3}-.0031138
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2}-.0475627{col 41}{space 2} .0773661{col 52}{space 1}   -0.61{col 61}{space 3}0.539{col 69}{space 4}-.1993827{col 82}{space 3} .1042574
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mcp age experiment2, at2(1 2 3 4)
{res}{txt}
{com}. 
. reg dvoteduda i.experiment2##i.agecat, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(11, 988)        =  {res}     3.49
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0345
                                                {txt}Root MSE          =    {res} .44625

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}                  dvoteduda{col 29}{c |} Coefficient{col 41}  std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .1429704{col 41}{space 2}  .062248{col 52}{space 1}    2.30{col 61}{space 3}0.022{col 69}{space 4} .0208169{col 82}{space 3} .2651239
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .0266913{col 41}{space 2} .0560609{col 52}{space 1}    0.48{col 61}{space 3}0.634{col 69}{space 4}-.0833207{col 82}{space 3} .1367034
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2}  .137987{col 41}{space 2} .0625072{col 52}{space 1}    2.21{col 61}{space 3}0.028{col 69}{space 4} .0153248{col 82}{space 3} .2606492
{txt}{space 27} {c |}
{space 21}agecat {c |}
{space 21}34-49  {c |}{col 29}{res}{space 2} .1693459{col 41}{space 2} .0641941{col 52}{space 1}    2.64{col 61}{space 3}0.008{col 69}{space 4} .0433735{col 82}{space 3} .2953183
{txt}{space 21}50-65  {c |}{col 29}{res}{space 2} .2320196{col 41}{space 2} .0668268{col 52}{space 1}    3.47{col 61}{space 3}0.001{col 69}{space 4} .1008807{col 82}{space 3} .3631584
{txt}{space 27} {c |}
{space 9}experiment2#agecat {c |}
{space 2}domestic messenger#34-49  {c |}{col 29}{res}{space 2}-.2622414{col 41}{space 2} .0911727{col 52}{space 1}   -2.88{col 61}{space 3}0.004{col 69}{space 4}-.4411558{col 82}{space 3}-.0833269
{txt}{space 2}domestic messenger#50-65  {c |}{col 29}{res}{space 2}-.1802515{col 41}{space 2} .1000735{col 52}{space 1}   -1.80{col 61}{space 3}0.072{col 69}{space 4}-.3766324{col 82}{space 3} .0161295
{txt}{space 2}domestic messenger+putin #{c |}
{space 21}34-49  {c |}{col 29}{res}{space 2} .0930171{col 41}{space 2} .0931535{col 52}{space 1}    1.00{col 61}{space 3}0.318{col 69}{space 4}-.0897843{col 82}{space 3} .2758185
{txt}{space 2}domestic messenger+putin #{c |}
{space 21}50-65  {c |}{col 29}{res}{space 2}-.0731048{col 41}{space 2} .0951007{col 52}{space 1}   -0.77{col 61}{space 3}0.442{col 69}{space 4}-.2597275{col 82}{space 3} .1135178
{txt}domestic messenger+putin.. #{c |}
{space 21}34-49  {c |}{col 29}{res}{space 2}-.1404534{col 41}{space 2} .0950377{col 52}{space 1}   -1.48{col 61}{space 3}0.140{col 69}{space 4}-.3269524{col 82}{space 3} .0460455
{txt}domestic messenger+putin.. #{c |}
{space 21}50-65  {c |}{col 29}{res}{space 2}-.2969546{col 41}{space 2} .0958449{col 52}{space 1}   -3.10{col 61}{space 3}0.002{col 69}{space 4}-.4850376{col 82}{space 3}-.1088717
{txt}{space 27} {c |}
{space 22}_cons {c |}{col 29}{res}{space 2} .1477273{col 41}{space 2}  .038054{col 52}{space 1}    3.88{col 61}{space 3}0.000{col 69}{space 4} .0730514{col 82}{space 3} .2224031
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins i.experiment2, at(agecat=(3))
{res}
{txt}{col 1}Adjusted predictions{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:1,000}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{lalign 4:At: }{space 0}{lalign 6:agecat} = {res:{ralign 1:3}}

{res}{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41} Delta-method
{col 29}{c |}     Margin{col 41}   std. err.{col 53}      t{col 61}   P>|t|{col 69}     [95% con{col 82}f. interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}experiment2 {c |}
{space 19}control  {c |}{col 29}{res}{space 2} .3797468{col 41}{space 2} .0549338{col 52}{space 1}    6.91{col 61}{space 3}0.000{col 69}{space 4} .2719465{col 82}{space 3} .4875471
{txt}{space 8}domestic messenger  {c |}{col 29}{res}{space 2} .3424658{col 41}{space 2} .0558763{col 52}{space 1}    6.13{col 61}{space 3}0.000{col 69}{space 4} .2328158{col 82}{space 3} .4521157
{txt}{space 2}domestic messenger+putin  {c |}{col 29}{res}{space 2} .3333333{col 41}{space 2} .0536992{col 52}{space 1}    6.21{col 61}{space 3}0.000{col 69}{space 4} .2279557{col 82}{space 3}  .438711
{txt}domestic messenger+putin..  {c |}{col 29}{res}{space 2} .2207792{col 41}{space 2} .0475538{col 52}{space 1}    4.64{col 61}{space 3}0.000{col 69}{space 4} .1274611{col 82}{space 3} .3140973
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. marginsplot 
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:experiment2}{p_end}
{res}{txt}
{com}. 
. *Mediation Analysis – Duda's Moral Authority and PO Support
. 
. cibar dudafav, over1(experiment2)
{res}{txt}
{com}. 
. *Mediating Effects of declines in Duda's Moral Authority on Voting PiS (OLS regression)
. 
. reg dvotetusk ukrainetxt dudatxt, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(2, 997)         =  {res}     6.26
                                                {txt}Prob > F          = {res}    0.0020
                                                {txt}R-squared         = {res}    0.0129
                                                {txt}Root MSE          =    {res} .48664

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2}     .126{col 26}{space 2} .0383176{col 37}{space 1}    3.29{col 46}{space 3}0.001{col 54}{space 4} .0508076{col 67}{space 3} .2011924
{txt}{space 5}dudatxt {c |}{col 14}{res}{space 2}    -.006{col 26}{space 2} .0372808{col 37}{space 1}   -0.16{col 46}{space 3}0.872{col 54}{space 4}-.0791578{col 67}{space 3} .0671578
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}     .366{col 26}{space 2} .0215751{col 37}{space 1}   16.96{col 46}{space 3}0.000{col 54}{space 4} .3236622{col 67}{space 3} .4083378
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dvotetusk ukrainetxt dudatxt dudafav, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(3, 996)         =  {res}   133.19
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2237
                                                {txt}Root MSE          =    {res} .43176

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   dvotetusk{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2} .0863194{col 26}{space 2} .0345287{col 37}{space 1}    2.50{col 46}{space 3}0.013{col 54}{space 4} .0185621{col 67}{space 3} .1540767
{txt}{space 5}dudatxt {c |}{col 14}{res}{space 2}-.0501204{col 26}{space 2} .0325935{col 37}{space 1}   -1.54{col 46}{space 3}0.124{col 54}{space 4}-.1140801{col 67}{space 3} .0138394
{txt}{space 5}dudafav {c |}{col 14}{res}{space 2}-.0693716{col 26}{space 2}  .003619{col 37}{space 1}  -19.17{col 46}{space 3}0.000{col 54}{space 4}-.0764734{col 67}{space 3}-.0622699
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6490362{col 26}{space 2} .0273377{col 37}{space 1}   23.74{col 46}{space 3}0.000{col 54}{space 4} .5953902{col 67}{space 3} .7026823
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg dudafav ukrainetxt dudatxt, robust

{txt}Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(2, 997)         =  {res}     4.36
                                                {txt}Prob > F          = {res}    0.0130
                                                {txt}R-squared         = {res}    0.0087
                                                {txt}Root MSE          =    {res} 3.2423

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     dudafav{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ukrainetxt {c |}{col 14}{res}{space 2}    -.572{col 26}{space 2} .2473266{col 37}{space 1}   -2.31{col 46}{space 3}0.021{col 54}{space 4} -1.05734{col 67}{space 3}-.0866595
{txt}{space 5}dudatxt {c |}{col 14}{res}{space 2}    -.636{col 26}{space 2} .2489832{col 37}{space 1}   -2.55{col 46}{space 3}0.011{col 54}{space 4}-1.124591{col 67}{space 3}-.1474088
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}     4.08{col 26}{space 2} .1500625{col 37}{space 1}   27.19{col 46}{space 3}0.000{col 54}{space 4} 3.785525{col 67}{space 3} 4.374475
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. sem (dudafav -> dvotetusk, ) (ukrainetxt -> dvotetusk, ) (ukrainetxt -> dudafav, ) (dudatxt -> dvotetusk, ) (dudatxt -> dudafav, ), nocapslatent vce(robust)
{res}{txt}
Endogenous variables
{p 2 12 2}Observed:{space 1}{res}dudafav dvotetusk{p_end}
{txt}
Exogenous variables
{p 2 12 2}Observed:{space 1}{res}ukrainetxt dudatxt{p_end}
{txt}
Fitting target model:
Iteration 0:{space 2}Log pseudolikelihood = {res: -4275.768}  
Iteration 1:{space 2}Log pseudolikelihood = {res: -4275.768}  

{col 1}Structural equation model{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:1,000}
{txt}{col 1}Estimation method: {res:ml}

{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 9:-4275.768}

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}dudafav      {col 17}{c |}
{space 5}ukrainetxt {c |}{col 17}{res}{space 2}    -.572{col 29}{space 2} .2470789{col 40}{space 1}   -2.32{col 49}{space 3}0.021{col 57}{space 4}-1.056266{col 70}{space 3}-.0877342
{txt}{space 8}dudatxt {c |}{col 17}{res}{space 2}    -.636{col 29}{space 2} .2487338{col 40}{space 1}   -2.56{col 49}{space 3}0.011{col 57}{space 4}-1.123509{col 70}{space 3}-.1484906
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}     4.08{col 29}{space 2} .1499122{col 40}{space 1}   27.22{col 49}{space 3}0.000{col 57}{space 4} 3.786177{col 70}{space 3} 4.373823
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}dvotetusk    {col 17}{c |}
{space 8}dudafav {c |}{col 17}{res}{space 2}-.0693716{col 29}{space 2} .0036136{col 40}{space 1}  -19.20{col 49}{space 3}0.000{col 57}{space 4}-.0764541{col 70}{space 3}-.0622892
{txt}{space 5}ukrainetxt {c |}{col 17}{res}{space 2} .0863194{col 29}{space 2} .0344768{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0187462{col 70}{space 3} .1538927
{txt}{space 8}dudatxt {c |}{col 17}{res}{space 2}-.0501204{col 29}{space 2} .0325445{col 40}{space 1}   -1.54{col 49}{space 3}0.124{col 57}{space 4}-.1139064{col 70}{space 3} .0136657
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6490362{col 29}{space 2} .0272966{col 40}{space 1}   23.78{col 49}{space 3}0.000{col 57}{space 4} .5955359{col 70}{space 3} .7025366
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}var(e.dudafav){c |}{col 17}{res}{space 2}   10.481{col 29}{space 2} .3493951{col 57}{space 4}  9.81809{col 70}{space 3} 11.18867
{txt}var(e.dvotetusk){c |}{col 17}{res}{space 2}  .185667{col 29}{space 2} .0053399{col 57}{space 4} .1754906{col 70}{space 3} .1964335
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. medsem, indep(ukrainetxt) med(dudafav) dep(dvotetusk) zlc rit rid

{txt}  Significance testing of indirect effect (unstandardised)
{c TLC}{hline 74}{c TRC}
{bf:  Estimates}{dup 10: }{c |}{bf:     Delta}{dup 7: }{c |} {bf:    Sobel}{dup 7: }{c |}{bf:  Monte Carlo}
{c LT}{hline 74}{c RT}
{res}  Indirect effect{col 22}{c |}     0.040{col 40}{c |}     0.040{col 58}{c |}     0.039

  Std. Err.{col 22}{c |}     0.017{col 40}{c |}     0.017{col 58}{c |}     0.017

  z-value{col 22}{c |}     2.316{col 40}{c |}     2.298{col 58}{c |}     2.252

  p-value{col 22}{c |}     0.021{col 40}{c |}     0.022{col 58}{c |}     0.024

  Conf. Interval{col 22}{c |} 0.006 , 0.073{col 40}{c |} 0.006 , 0.074{col 58}{c |} 0.005 , 0.074
{txt}{c LT}{hline 74}{c RT}

  Baron and Kenny approach to testing mediation
{res}  STEP 1 - dudafav:ukrainetxt (X -> M) with B=-0.572 and p=0.021
  STEP 2 - dvotetusk:dudafav (M -> Y) with B=-0.069 and p=0.000
  STEP 3 - dvotetusk:ukrainetxt (X -> Y) with B=0.086 and p=0.012
{txt}           As STEP 1, STEP 2 and STEP 3 as well as the Sobel's test above
           are significant the mediation is partial!

  Zhao, Lynch & Chen's approach to testing mediation
{res}  STEP 1 - dvotetusk:ukrainetxt (X -> Y) with B=0.086 and p=0.012
{txt}           As the Monte Carlo test above is significant, STEP 1 is
           significant and their coefficients point in same direction,
           you have complementary mediation (partial mediation)!

  RIT  =   (Indirect effect / Total effect)
{res}           (0.040 / 0.126) = 0.315
{txt}           Meaning that about 31 % of the effect of ukrainetxt
           on dvotetusk is mediated by dudafav!

  RID  =   (Indirect effect / Direct effect)
{res}           (0.040 / 0.086) = 0.460
{txt}           That is, the mediated effect is about 0.5 times as
           large as the direct effect of ukrainetxt on dvotetusk!
{c BLC}{hline 74}{c BRC}
  Note: to read more about this package{stata "help medsem": help medsem}

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\swhitt\Desktop\EJPR Poland Replication Data\EJPR Poland replication log file.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}14 Mar 2025, 09:15:17
{txt}{.-}
{smcl}
{txt}{sf}{ul off}